# OpenMLHub:  Machine Learning Model Tracking and Validation

## Overview

Welcome to the OpenMLHub Client – your go-to solution for tracking and validating machine learning models for scientific research. This project facilitates seamless integration with OpenMLHub, enabling you to manage and assess your models efficiently.

## Features

- **Model Tracking**: Easily track the performance of your machine learning models over time.
- **Validation Support**: Streamline the validation process for scientific research purposes.
- **OpenMLHub Integration**: Connect and collaborate with the OpenMLHub community effortlessly.
- **User-Friendly Interface**: Intuitive design for a smooth user experience.
- **Scalable Architecture**: Built for scalability to accommodate various project sizes.

## Getting Started

Follow these steps to get started with the OpenMLHub Client:

1. **Installation**:
   ```
   pip install openmlhub
   ```

2. **Configuration**:
   - Obtain your OpenMLHub API key.
   - Set up your configuration file with the API key.

3. **Usage**:
   ```python
   from openmlhub import OpenMLHub

   client = OpenMLHubClient()
   ```

## Examples

```python
# Track a new model
model_id = client.track_model(model_name='My_Model', algorithm='Random Forest', dataset='iris')

# Validate the model
validation_result = client.validate_model(model_id)

# Retrieve model details
model_details = client.get_model_details(model_id)
```

## Contributing

We welcome contributions to enhance the OpenMLHub Client. To contribute:

1. Fork the repository.
2. Create a new branch: `git checkout -b feature/your-feature`.
3. Commit your changes: `git commit -m 'Add your feature'`.
4. Push to the branch: `git push origin feature/your-feature`.
5. Open a pull request.

## License

This project is licensed under the [MIT License](LICENSE.md).

## Contact

For any inquiries or support, contact us at [support@openmlhubclient.com](mailto:support@openmlhubclient.com).

Happy modeling and tracking! 🚀
